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The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 3 million. For the duplicated benchmarks, the same random values are repeated an average of 5 times.
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:idprefix: benchmarks_
:idprefix: benchmarks_
= Benchmarks
= 基准测试
boost::unordered_[multi]set
boost::unordered_[multi]set
All benchmarks were created using `unordered_set<unsigned int>` (non-duplicate) and `unordered_multiset<unsigned int>` (duplicate). The source code can be https://github.com/boostorg/boost_unordered_benchmarks/tree/boost_unordered_set[found here^].
所有基准测试均使用 `unordered++_++set++&lt;++unsigned int++&gt;++`(非重复元素） 和 `unordered++_++multiset++&lt;++unsigned int++&gt;++` （重复元素）创建。源代码可 https://github.com/boostorg/boost_unordered_benchmarks/tree/boost_unordered_set[在此处获取] 。
The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 3 million. For the duplicated benchmarks, the same random values are repeated an average of 5 times.
插入基准测试会插入 `n` 个随机值，其中 `n` 的范围在10,000至300万之间。在重复值测试场景中，同一组随机值会平均重复插入 5 次。
The erasure benchmarks erase all `n` elements randomly until the container is empty. Erasure by key uses `erase(const key_type&)` to remove entire groups of equivalent elements in each operation.
在擦除基准测试中，随机删除所有 `n` 个元素直至容器为空。通过键擦除操作使用 `erase(const key++_++type&amp;)` 方法，每次调用将移除整个等效元素组。
:14
The successful lookup benchmarks are done by looking up all `n` values, in their original insertion order.
成功查找基准测试通过按照元素的原始插入顺序查找全部 `n` 个值来完成。
:16
The unsuccessful lookup benchmarks use `n` randomly generated integers but using a different seed value.
未命中查找基准测试使用不同种子值生成的 `n` 个随机整数进行。
GCC 12 + libstdc++-v3, x64
GCC 12 + libstdc++-v3, x64
:20
Insertion
插入
image::benchmarks-set/gcc/running insertion.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice non-unique.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice non-unique.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice non-unique.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice non-unique.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice non-unique 5.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice non-unique 5.png,window=_blank]
h|non-duplicate elements h|duplicate elements h|duplicate elements, + max load factor 5 |===
h|非重复元素 h|重复元素 h|重复元素, + 最大负载因子 5 |===
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png,window=_blank]
:44
h|non-duplicate elements, + prior `reserve` h|duplicate elements, + prior `reserve` h|duplicate elements, + max load factor 5, + prior `reserve`
h|非重复元素, + 预先 `reserve` h|重复元素, + 预先 `reserve` h|重复元素, + 最大负载因子 5, + 预先 `reserve`
:54
Erasure
擦除
image::benchmarks-set/gcc/scattered erasure.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/scattered erasure.xlsx.practice.png,window=_blank]
image::benchmarks-set/gcc/scattered erasure.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/scattered erasure.xlsx.practice.png,window=_blank]
English Chinese (Simplified Han script) Actions
image::benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique 5.png]
image::benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/clang_libcpp/scattered successful looukp.xlsx.practice non-unique 5.png]
boost::unordered_(flat|node)_map
boost::unordered_(flat|node)_map
The erasure benchmarks erase traverse the `n` elements and erase those with odd key (50% on average).
擦除基准测试会遍历全部 `n` 个元素，并删除其中键值为奇数的元素（平均约占50%）。
image::benchmarks-flat_map/clang-x86/Running insertion.xlsx.plot.png[width=250,window=_blank,link=_images/benchmarks-flat_map/clang-x86/Running insertion.xlsx.plot.png]
image::benchmarks-flat_map/clang-x86/Running insertion.xlsx.plot.png[width=250,window=_blank,link=_images/benchmarks-flat_map/clang-x86/Running insertion.xlsx.plot.png]
image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.99.png"]
image::benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-x64/Parallel workload.xlsx.5M, 0.99.png"]
image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.99.png"]
image::benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x64/Parallel workload.xlsx.5M, 0.99.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.01.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.01.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.99.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.500k, 0.99.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.01.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.01.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.5.png"]
image::benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.5.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/clang-arm64/Parallel workload.xlsx.5M, 0.5.png"]
image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.01.png"]
image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.01.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.01.png"]
image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.5.png"]
image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.5.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.5.png"]
image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.99.png"]
image::benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.99.png[width=250,window=_blank,link="_images/benchmarks-concurrent_map/vs-x86/Parallel workload.xlsx.500k, 0.99.png"]
boost::unordered_[multi]set
boost::unordered_[multi]set
All benchmarks were created using `unordered_set<unsigned int>` (non-duplicate) and `unordered_multiset<unsigned int>` (duplicate). The source code can be https://github.com/boostorg/boost_unordered_benchmarks/tree/boost_unordered_set[found here^].
所有基准测试均使用 `unordered++_++set++&lt;++unsigned int++&gt;++`(非重复元素） 和 `unordered++_++multiset++&lt;++unsigned int++&gt;++` （重复元素）创建。源代码可 https://github.com/boostorg/boost_unordered_benchmarks/tree/boost_unordered_set[在此处获取] 。
The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 3 million. For the duplicated benchmarks, the same random values are repeated an average of 5 times.
插入基准测试会插入 `n` 个随机值，其中 `n` 的范围在10,000至300万之间。在重复值测试场景中，同一组随机值会平均重复插入 5 次。
h|non-duplicate elements h|duplicate elements h|duplicate elements, + max load factor 5 |===
h|非重复元素 h|重复元素 h|重复元素, + 最大负载因子 5 |===
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png,window=_blank]
image::benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png[width=250,link=_images/benchmarks-set/gcc/running insertion.xlsx.practice norehash non-unique 5.png,window=_blank]
image::benchmarks-set/gcc/scattered erasure.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/scattered erasure.xlsx.practice.png,window=_blank]
image::benchmarks-set/gcc/scattered erasure.xlsx.practice.png[width=250,link=_images/benchmarks-set/gcc/scattered erasure.xlsx.practice.png,window=_blank]
image::benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique 5.png]
image::benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/clang_libcpp/scattered erasure.xlsx.practice non-unique 5.png]
image::benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique.png[width=250,link=_images/benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique.png,window=_blank]
image::benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique.png[width=250,link=_images/benchmarks-set/clang_libcpp/scattered erasure by key.xlsx.practice non-unique.png,window=_blank]
image::benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice.png]
image::benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/clang_libcpp/scattered unsuccessful looukp.xlsx.practice.png]
image::benchmarks-set/vs/running insertion.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/vs/running insertion.xlsx.practice.png]
image::benchmarks-set/vs/running insertion.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/vs/running insertion.xlsx.practice.png]
image::benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique.png[width=250,window=_blank,link=_images/benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique.png]
image::benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique.png[width=250,window=_blank,link=_images/benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique.png]
image::benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique 5.png]
image::benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/vs/running insertion.xlsx.practice norehash non-unique 5.png]
image::benchmarks-set/vs/scattered erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered erasure.xlsx.practice non-unique 5.png]
image::benchmarks-set/vs/scattered erasure.xlsx.practice non-unique 5.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered erasure.xlsx.practice non-unique 5.png]
image::benchmarks-set/vs/scattered successful looukp.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered successful looukp.xlsx.practice.png]
image::benchmarks-set/vs/scattered successful looukp.xlsx.practice.png[width=250,window=_blank,link=_images/benchmarks-set/vs/scattered successful looukp.xlsx.practice.png]
`boost::unordered_map<uint64_t, uint64_t>`
`boost::unordered_map<uint64_t, uint64_t="">`</uint64_t,>

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Translation uploaded
The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 3 million. For the duplicated benchmarks, the same random values are repeated an average of 5 times.
The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 3 million. For the duplicated benchmarks, the same random values are repeated an average of 5 times.插入基准测试会插入 `n` 个随机值，其中 `n` 的范围在10,000至300万之间。在重复值测试场景中，同一组随机值会平均重复插入 5 次。
06/05/2026
User avatar admin

String added in the repository
The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 3 million. For the duplicated benchmarks, the same random values are repeated an average of 5 times.
The insertion benchmarks insert `n` random values, where `n` is between 10,000 and 3 million. For the duplicated benchmarks, the same random values are repeated an average of 5 times.
06/05/2026
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safe-html, strict-same
Unit identifier
50578
Source string location
:10
String age
06/05/2026
Last updated
06/06/2026
Source string age
06/05/2026
Translation file AsciiDoc file
doc/modules/ROOT/pages/benchmarks_zh_Hans.adoc, string 5